A novel causal structure-based framework for comparing a basin-wide water–energy–food–ecology nexus applied to the data-limited Amu Darya and Syr Darya river basins

Abstract

Abstract. The previous comparative studies on watersheds were mostly based on the comparison of dispersive characteristics, which lacked systemicity and causality. We proposed a causal structure-based framework for basin comparison based on the Bayesian network (BN) and focus on the basin-scale water–energy–food–ecology (WEFE) nexus. We applied it to the Syr Darya River basin (SDB) and the Amu Darya River basin (ADB), of which poor water management caused the Aral Sea disaster. The causality of the nexus was effectively compared and universality of this framework was discussed. In terms of changes in the nexus, the sensitive factor for the water supplied to the Aral Sea changed from the agricultural development during the Soviet Union period to the disputes in the WEFE nexus after the disintegration. The water–energy contradiction of the SDB is more severe than that of the ADB, partly due to the higher upstream reservoir interception capacity. It further made management of the winter surplus water downstream of the SDB more controversial. Due to this, the water–food–ecology conflict between downstream countries may escalate and turn into a long-term chronic problem. Reducing water inflow to depressions and improving the planting structure prove beneficial to the Aral Sea ecology, and this effect of the SDB is more significant. The construction of reservoirs on the Panj River of the upstream ADB should be cautious to avoid an intense water–energy conflict such as the SDB's. It is also necessary to promote the water-saving drip irrigation and to strengthen the cooperation.

Revisiting and attributing the global controls on terrestrial ecosystem functions of climate and plant traits at FLUXNET sites with causal networks

“…The effective implementation of BN-based causal analysis may depend on the reliability of the causal relationships provided by expert knowledge (directional links between variables). We can establish the connection relationships and network structures between variables from expert knowledge and assign the specific quantification of the connection relationships (conditional probability tables) to the observations and data (Shi et al, 2021a). In the future, we can revisit the linkages of ecosystem functions with climate and environmental systems using BN-based causal analysis to understand the strength and mechanisms of the relationships between direct, indirect, and remotely related effects of variables.…”

Consideration of the Environment in Water-Energy-Food Nexus Research in the Aral Sea Basin

“…Some papers, e.g., Graham et al [13], also explored the complex interconnections between water, food, and energy security and confronted the substantial problem of fisheries in Central Asia. Additionally, Shi et al [14,52] employed Bayesian networks and causal structure-based frameworks for water resource analysis and management. Basin-wide coverage 25…”

“…For instance, Khamidov et al [50] investigated the impact of soil salinity, accentuated by climate change, on WEF resources. Likewise, Shi et al [14,52] and Qin et al [15] elucidated aspects of the WEF nexus intertwined with ecological considerations. Moreover, the limitations in data availability and its fragmented nature stand as formidable obstacles constraining the breadth of the research scope in the study area.…”

Analysis of the Impacts of Environmental Factors on Rat Hole Density in the Northern Slope of the Tienshan Mountains with Satellite Remote Sensing Data

“…Different vertical elevation zones correspond to different landscape types and ecosystems. The unique natural conditions of NTXJ make it a typical representative of large-scale mountain-oasis-desert ecosystems in temperate arid regions of Central Asia [30].…”